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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
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and refine algorithms and models for large-scale language processing tasks, with a focus on healthcare data Contribute to developing new models, techniques and methods for clinical machine learning
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the origin of seed gene networks”. This project aims to use reverse genetics, cross-species complementation and single cell next-generation sequencing approaches to investigate how the gene networks
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the prevalence and risk of modern slavery. There will be a focus on Bayesian nonparametric methods and practical development of MCMC algorithms that can be applied to data. Translating the project findings
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development of mathematical models and algorithms for the analysis of biopharmaceutical manufacturing processes with a focus on assuring safety and alignment of machine learning models with the expected
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genetic events with PRMT5 inhibitors in Ewing sarcoma, focusing on the DNA damage response and splicing. We require a highly motivated and organised individual that is willing to meet deadlines. Principal
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cytoplasmic lysyl hydroxylase that modifies a translation factor GTPase (Nature Chem Bio 2018; Genet Med 2023; Structure 2024; Cell Mol Life Sci 2021). Here in this highly competitive BBSRC-funded project, you